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Papers

Effect of increasing accuracy of genomic evaluations on economic efficiency of dairy cattle breeding programmes

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Pages 379-385 | Received 01 Feb 2016, Accepted 19 May 2016, Published online: 10 Aug 2016

References

  • Börner V, Reinsch N. 2012. Optimising multistage dairy cattle breeding schemes including genomic selection using decorrelated or optimum selection indices. Genet Sel Evol. 44:1–11.
  • Chegini A, Shadparvar AA, Ghavi Hossein-Zadeh N. 2013. Genetic trends for milk yield, persistency of milk yield, somatic cell count and calving interval in Holstein dairy cows of Iran. Iran J Appl Anim Sci. 3:503–508.
  • Daetwyler HD, Pong-Wong R, Villanueva B, Woolliams JA. 2010. The impact of genetic architecture on genome-wide evaluation methods. Genetics. 185:1021–1031.
  • Dickerson GE. 1978. Animal size and efficiency: basic concepts. Anim Prod. 27:367–379.
  • Erbe M, Gredler B, Seefried FR, Bapst B, Simianer H. 2013. A function accounting for training set size and marker density to model the average accuracy of genomic prediction. PLoS One. 8:e81046.
  • Falconer DS, Mackay TFC. 1996. Introduction to quantitative genetics. 4th rev. ed. Harlow, UK: Longman Group, Ltd.
  • Ghavi Hossein-Zadeh N. 2011. Genetic parameters and trends for calving interval in the first three lactations of Iranian Holsteins. Trop Anim Health Prod. 43:1111–1115.
  • Goddard M. 2009. Genomic selection: prediction of accuracy and maximisation of long term response. Genetica. 136:245–257.
  • Goddard ME, Hayes BJ, Meuwissen THE. 2011. Using the genomic relationship matrix to predict the accuracy of genomic selection. J Anim Breed Genet. 128:409–421.
  • Goddard MG, Smith TFC. 1990. Optimum number of bull sires in dairy cattle breeding. J Dairy Sci. 73: 1113–1122.
  • Gonzalez-Recio O, Coffey MP, Pryce JE. 2014. On the value of the phenotypes in the genomic era. J Dairy Sci. 97:1–11.
  • Hill WG. 1974. Prediction and evaluation of response to selection with overlapping generations. Anim Prod. 18:174–189.
  • Joezy-Shekalgorabi S, Shadparvar AA, Vaez Torshizi R, Shahrebabak M, Jorjani H. 2010. Genetic analysis of a conventional progeny testing. In: Proceedings of the 9th WCGALP; Leipzig, Germany; paper 220, 4 pp.
  • König S, Simianer H, Willam A. 2009. Economic evaluation of genomic breeding programs. J Dairy Sci. 92:382–391.
  • König S, Swalve HH. 2009. Application of selection index calculations to determine selection strategies in genomic breeding programs. J Dairy Sci. 92:5292–5303.
  • Liu Z, Seefried FR, Reinhardt F, Rensing S, Thaller G, Reents R. 2011. Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction. Genet Sel Evol. 43:19–32.
  • Meuwissen THE, Hayes B, Goddard ME. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics. 157:1819–1829.
  • Schaeffer LR. 2006. Strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet. 123:218–223.
  • Su G, Nielsen US, Wiggans G, Aamand GP, Guldbrandtsen B, Lund MS. 2014. Improving genomic prediction for Danish Jersey using a joint Danish-US reference population. In: Proceedings of the 10th World Congress on Genetics Applied to Livestock Production; Vancouver, BC, Canada; Comm. 060. [cited 2015 Jan 28] Available from: https://asas.org/docs/default-source/wcgalp-proceedings-oral/060_paper_8823_manuscript_396_0.pdf.
  • Thomasen JR, Egger-Danner C, Willam A, Guldbrandtsen B, Lund MS, Sørensen AC. 2014. Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit. J Dairy Sci. 97:458–470.
  • Zhou L, Ding X, Zhang Q, Wang Y, Lund MS, Su G. 2013. Consistency of linkage disequilibrium between Chinese and Nordic Holsteins and genomic prediction for Chinese Holsteins using a joint reference population. Genet Sel Evol. 45:7–14.